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Robust supply chain network design: an optimization model with real world application

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Abstract

This paper presents a robust optimization model for the design of a supply chain facing uncertainty in demand, supply capacity and major cost data including transportation and shortage cost parameters. We first present a base model that aims to determine the strategic ‘location’ and tactical ‘allocation’ decisions for a deterministic four-tier supply chain. The model is then extended to incorporate uncertainty in key input parameters using a robust optimization approach that can overcome the limitations of scenario-based solution methods in a tractable way, i.e. without excessive changes in complexity of the underlying base deterministic model. The application of the approach is investigated in an actual case study where real data is utilized to design a bread supply chain network. Numerical results obtained from model implementation and sensitivity analysis experiments arrive at important managerial insights and practical implications.

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Authors and Affiliations

  1. Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran

    Shiva Zokaee, Armin Jabbarzadeh & Seyed Jafar Sadjadi

  2. Institute of Transport and Logistics Studies (ITLS), The University of Sydney Business School, Sydney, Australia

    Behnam Fahimnia

Authors
  1. Shiva Zokaee
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  2. Armin Jabbarzadeh
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  3. Behnam Fahimnia
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  4. Seyed Jafar Sadjadi
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Correspondence to Behnam Fahimnia.

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Zokaee, S., Jabbarzadeh, A., Fahimnia, B. et al. Robust supply chain network design: an optimization model with real world application. Ann Oper Res 257, 15–44 (2017). https://doi.org/10.1007/s10479-014-1756-6

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